Distributed Zero-Sum Differential Game for Multi-Agent Nonlinear Systems via Adaptive Dynamic Programming

Jingliang Sun; Chunsheng Liu

doi:10.23919/ChiCC.2018.8484118

Distributed Zero-Sum Differential Game for Multi-Agent Nonlinear Systems via Adaptive Dynamic Programming

Jingliang Sun, Chunsheng Liu

Nanjing University of Aeronautics and Astronautics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Citations (Scopus)

Abstract

In this paper, the distributed zero-sum differential game problem for multi-agent nonlinear systems is investigated by using adaptive dynamic programming (ADP) technique, which brings together the distributed control, zero-sum differential graphical game and ADP. To find the cooperative Nash-equilibrium solutions of the associated coupled Hamilton-Jacobi-Isaacs (HJI) equations, the ADP technique is employed, in which a critic network is constructed to approximate the cooperative cost function online with a novel updating law. By utilizing the Lyapunov direct method, the closed-loop system and weight estimation errors are guaranteed to be uniformly ultimately bounded (UUB). Finally, simulation results demonstrate the effectiveness of the proposed method.

Original language	English
Title of host publication	Proceedings of the 37th Chinese Control Conference, CCC 2018
Editors	Xin Chen, Qianchuan Zhao
Publisher	IEEE Computer Society
Pages	2770-2775
Number of pages	6
ISBN (Electronic)	9789881563941
DOIs	https://doi.org/10.23919/ChiCC.2018.8484118
Publication status	Published - 5 Oct 2018
Externally published	Yes
Event	37th Chinese Control Conference, CCC 2018 - Wuhan, China Duration: 25 Jul 2018 → 27 Jul 2018

Publication series

Name	Chinese Control Conference, CCC
Volume	2018-July
ISSN (Print)	1934-1768
ISSN (Electronic)	2161-2927

Conference

Conference	37th Chinese Control Conference, CCC 2018
Country/Territory	China
City	Wuhan
Period	25/07/18 → 27/07/18

Keywords

Adaptive dynamic programming (ADP)
Distributed control
Multi-agent system (MAS)
Zero-sum differential game

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10.23919/ChiCC.2018.8484118

Cite this

Sun, J., & Liu, C. (2018). Distributed Zero-Sum Differential Game for Multi-Agent Nonlinear Systems via Adaptive Dynamic Programming. In X. Chen, & Q. Zhao (Eds.), Proceedings of the 37th Chinese Control Conference, CCC 2018 (pp. 2770-2775). Article 8484118 (Chinese Control Conference, CCC; Vol. 2018-July). IEEE Computer Society. https://doi.org/10.23919/ChiCC.2018.8484118

@inproceedings{9e9a8071cc104b8b88147135fbb9e6ed,

title = "Distributed Zero-Sum Differential Game for Multi-Agent Nonlinear Systems via Adaptive Dynamic Programming",

abstract = "In this paper, the distributed zero-sum differential game problem for multi-agent nonlinear systems is investigated by using adaptive dynamic programming (ADP) technique, which brings together the distributed control, zero-sum differential graphical game and ADP. To find the cooperative Nash-equilibrium solutions of the associated coupled Hamilton-Jacobi-Isaacs (HJI) equations, the ADP technique is employed, in which a critic network is constructed to approximate the cooperative cost function online with a novel updating law. By utilizing the Lyapunov direct method, the closed-loop system and weight estimation errors are guaranteed to be uniformly ultimately bounded (UUB). Finally, simulation results demonstrate the effectiveness of the proposed method.",

keywords = "Adaptive dynamic programming (ADP), Distributed control, Multi-agent system (MAS), Zero-sum differential game",

author = "Jingliang Sun and Chunsheng Liu",

note = "Publisher Copyright: {\textcopyright} 2018 Technical Committee on Control Theory, Chinese Association of Automation.; 37th Chinese Control Conference, CCC 2018 ; Conference date: 25-07-2018 Through 27-07-2018",

year = "2018",

month = oct,

day = "5",

doi = "10.23919/ChiCC.2018.8484118",

language = "English",

series = "Chinese Control Conference, CCC",

publisher = "IEEE Computer Society",

pages = "2770--2775",

editor = "Xin Chen and Qianchuan Zhao",

booktitle = "Proceedings of the 37th Chinese Control Conference, CCC 2018",

address = "United States",

}

Sun, J & Liu, C 2018, Distributed Zero-Sum Differential Game for Multi-Agent Nonlinear Systems via Adaptive Dynamic Programming. in X Chen & Q Zhao (eds), Proceedings of the 37th Chinese Control Conference, CCC 2018., 8484118, Chinese Control Conference, CCC, vol. 2018-July, IEEE Computer Society, pp. 2770-2775, 37th Chinese Control Conference, CCC 2018, Wuhan, China, 25/07/18. https://doi.org/10.23919/ChiCC.2018.8484118

Distributed Zero-Sum Differential Game for Multi-Agent Nonlinear Systems via Adaptive Dynamic Programming. / Sun, Jingliang; Liu, Chunsheng.
Proceedings of the 37th Chinese Control Conference, CCC 2018. ed. / Xin Chen; Qianchuan Zhao. IEEE Computer Society, 2018. p. 2770-2775 8484118 (Chinese Control Conference, CCC; Vol. 2018-July).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Distributed Zero-Sum Differential Game for Multi-Agent Nonlinear Systems via Adaptive Dynamic Programming

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PY - 2018/10/5

Y1 - 2018/10/5

N2 - In this paper, the distributed zero-sum differential game problem for multi-agent nonlinear systems is investigated by using adaptive dynamic programming (ADP) technique, which brings together the distributed control, zero-sum differential graphical game and ADP. To find the cooperative Nash-equilibrium solutions of the associated coupled Hamilton-Jacobi-Isaacs (HJI) equations, the ADP technique is employed, in which a critic network is constructed to approximate the cooperative cost function online with a novel updating law. By utilizing the Lyapunov direct method, the closed-loop system and weight estimation errors are guaranteed to be uniformly ultimately bounded (UUB). Finally, simulation results demonstrate the effectiveness of the proposed method.

AB - In this paper, the distributed zero-sum differential game problem for multi-agent nonlinear systems is investigated by using adaptive dynamic programming (ADP) technique, which brings together the distributed control, zero-sum differential graphical game and ADP. To find the cooperative Nash-equilibrium solutions of the associated coupled Hamilton-Jacobi-Isaacs (HJI) equations, the ADP technique is employed, in which a critic network is constructed to approximate the cooperative cost function online with a novel updating law. By utilizing the Lyapunov direct method, the closed-loop system and weight estimation errors are guaranteed to be uniformly ultimately bounded (UUB). Finally, simulation results demonstrate the effectiveness of the proposed method.

KW - Adaptive dynamic programming (ADP)

KW - Distributed control

KW - Multi-agent system (MAS)

KW - Zero-sum differential game

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Distributed Zero-Sum Differential Game for Multi-Agent Nonlinear Systems via Adaptive Dynamic Programming

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